Papers by Ruixi Lin

3 papers
Mind the Biases: Quantifying Cognitive Biases in Language Model Prompting (2023.findings-acl)

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Challenge: Cognitive biases in the human decision making process can lead to flawed responses when we are under uncertainty.
Approach: They propose to expose cognitive biases on results of language model prompting which display bias modes resembling cognitive bias.
Outcome: The proposed methods show that a toning-down transformation of the drug-drug description in a prompt can elicit a bias similar to the framing effect, warning users to distrust when prompting language models for answers.
TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval (2026.acl-long)

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Challenge: Existing approaches to enzyme–reaction retrieval suffer from poor generalization across tasks and distributions . TIGER is a text-informed generalized enzyme-reaction retrieval framework that bridges enzymes and biochemical reactions.
Approach: They propose a text-informed generalized enzyme-reaction retrieval framework that leverages protein-to-text generation models to distill textual knowledge from enzyme sequences.
Outcome: The proposed framework outperforms state-of-the-art methods in enzyme–reaction retrieval tasks and distributions.
Does BERT Know that the IS-A Relation Is Transitive? (2022.acl-short)

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Challenge: Recent studies suggest pre-trained BERT can capture lexico-semantic clues from words in context.
Approach: They examine word senses and the transitive property of IS-A relation . they aim to quantify how much BERT agrees with transitivity property .
Outcome: The proposed model can capture lexico-semantic clues from words in context . but to what extent it captures transitive nature of some lexical relations is unclear .

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